Wolters Kluwer N.V. (AEX: WKL) is a global leader in information services and solutions for professionals in the health, tax and accounting, risk and compliance, finance and legal sectors. We help our customers make critical decisions every day by providing expert solutions that combine deep domain knowledge with specialized technology and services. Wolters Kluwer reported 2017 annual revenues of €4.4billion. The company, headquartered in Alphen aan den Rijn, the Netherlands, serves customers in over 180 countries, maintains operations in over 40 countries and employs 19,000 people worldwide. Wolters Kluwer shares are listed on Euronext Amsterdam (WKL) and are included in the AEX and Euronext 100 indices. For more information about our solutions and organization, visit www.wolterskluwer.com, follow us on Twitter, Facebook, and LinkedIn.

In our specific business unit, Wolters Kluwer Governance, Risk and Compliance we possess deep insight into the industry, providing governance, risk and compliance programs and solutions to more than 15,000 financial services organizations worldwide. More than 400 in-house experts - former regulators and compliance officers, risk analysts, lawyers and financial industry specialists – embed their knowledge and expertise in every service or solution so that financial organizations can be confident they are managing their organization's Finance, Risk and Regulation needs effectively. Despite rapidly changing industry conditions, financial organizations can rest assured knowing that Wolters Kluwer is able to invest and quickly respond to market needs, with financial stability for the long term.

Requirements

Education

Graduate degree (MS or PhD) in Computer Science, Engineering, Mathematics or equivalent; specializing in machine learning or a related field

Experience

2+ years' experience in Data Science, NLP, Machine Learning, and/or Deep Learning
Coding proficiency in at least one modern programming language such as Python, R, or Java
Active listening skills, and deep analytical ability are required to develop and define key business questions and to build data sets that answer those questions
Demonstrated ability to function in distributed and multi-disciplinary teams across technology and business
Strong verbal and written communication skills and effective presentation skills
Preferred Qualifications

Industry experience as a Data Scientist with a track record of manipulating, processing, and extracting value from large datasets
Experience with developing and deploying machine learning pipelines to production
Experience in software development
Experience with XML, XML Schema, XSLT
Experience with SPARQL and other NoSQL data bases a plus
Experience with semantics web technologies such as RDF, OWL, RDFa a plus

Responsibilities

Essential Duties and Responsibilities

Develop Predictive models with Deep Learning networks, Gradient Boosting, Random Forest, SVM, and Logistic Regression using both generative and discriminative algorithms
Perform data insights analysis using clustering, agglomerative clustering, graph-based clustering, and analysis
Define and develop features (abstract), selections, and ranking with PCA, Ridge/Lasso, or Deep Learning
Model time series data for forecasting with Holt-Winters, ARMA/ARIMA and other relevant models and including uncertainty estimation (Prediction Intervals)
Engage as a key member of the advanced technology team to investigate solutions and support their delivery to production
Rapidly research, experiment and build prototypes using commercial, Open Source and proprietary solutions for machine learning, deep learning and NLP including an assessment of production suitability
Develop data science solutions in a highly collaborative team
Communicate prototype results in an actionable form, including lessons learned and next steps for technical teams in the AI CoE and other technology groups
Identify and drive best practices for data science solutions development
A self-starter who can align the technology solution with a business goal
Assess various machine learning frameworks and packages
Collaborate effectively with other data sciences teams across Wolters Kluwer to align on direction and leverage existing tools and knowledge
Author peer reviewed journal articles and white papers related to the Data Science solutions
Education

Graduate degree (MS or PhD) in Computer Science, Engineering, Mathematics or equivalent; specializing in machine learning or a related field

Other info

We are searching for a data scientist who is passionate about technology and solving real world problems by leveraging advanced technologies; such as natural language processing, machine learning and deep learning. ou should be willing to take on challenges of unknown dimensions, and work hand in hand with business, product leaders, customers, and developers. You will need to have very strong technical skills in data sciences and a proven ability to deliver products to the market.

Reporting into the Advanced Technology team, this role is crucial to the continued growth and evolution of one of the leading companies providing expert solutions to the healthcare, compliance, legal and tax markets globally.